Improving Scalability and Maintenance of Software for High-Performance Scientific Computing by Combining MDE and Frameworks

Palyart, Marc; Lugato, David; Ober, Iulian; Bruel, Jean‐Michel

doi:10.1007/978-3-642-24485-8_16

Cited by 10 publications

(13 citation statements)

References 11 publications

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“…In this section we give some glimpses into this approach. For more details the reader is referred to [14]. The aim of this section is to report on the feasibility of using MDE in HPC applications, and to show how using this approach opens the way to the use of some features, that are not traditionally used by HPC applications, but are used on a larger scale in the development of real-time and embedded applications -fields that report success stories of adopting MDE since a few years ago.…”

Section: Hpcml: a Dsml For Fortranmentioning

confidence: 98%

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MDE in Practice for Computational Science

Bruel

Combemale

Ober

et al. 2015

Procedia Computer Science

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The complex problems that computational science addresses are more and more benefiting from the progress of computing facilities (simulators, librairies, accessible languages, . . . ). Nevertheless, the actual solutions call for several improvements. Among those, we address in this paper the needs for leveraging on knowledge and expertise by focusing on Domain-Specific Modeling Languages application. In this vision paper we illustrate, through concrete experiments, how the last DSML research help getting closer the problem and implementation spaces.

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Section: Hpcml: a Dsml For Fortranmentioning

confidence: 98%

“…Synopsis of the approach Our approach for adding abstraction in HPC applications, approach called MDE4HPC, is overviewed in [14]. MDE4HPC tackles the development complexity of scientific application, with intensive use of numerical simulation, by means of raising abstraction.…”

Section: Hpcml: a Dsml For Fortranmentioning

confidence: 99%

MDE in Practice for Computational Science

Bruel

Combemale

Ober

et al. 2015

Procedia Computer Science

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“…MDE is used to develop complex systems involving several views of software systems [1], including modeling complex non-functional properties such as maintenability [34] and scalability [24]. It has been applied in diverse areas such as robotics [31], and vehicle control software [27], among others.…”

Section: Related Workmentioning

confidence: 99%

Using megamodeling to improve industrial adoption of complex MDE solutions

Bastarrica

Simmonds

Silvestre

2014

Proceedings of the 6th International Workshop on Modeling in Software Engineering

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Companies formalize their software processes as a way of organizing their development projects. As each project has its own requirements and objectives, a family of processes is required in practice, in order to ensure that each project is handled appropriately. This family may be a collection of predefined processes, but can also be automatically generated by tailoring a general process to a project's context which requires formalization and tool support to be successful. Model-driven engineering provides a formal framework for defining the models and transformations required for automated process tailoring, but various types of models must be specified and evolved, limiting the industrial adoption of this approach. To address this problem, in this paper we propose a megamodel for automated process tailoring. Megamodeling provides an integrating framework for modeling in the large, including the definition and evolution of all models and transformations required for tailoring while hiding complexity. We report the application of our approach to the software development process of Rhiscom, a small Chilean company.

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“…The choice of MDE seemed natural as many of these requirements are now beginning to be recognized as MDE benefits in the literature [10]. In addition this development was part of a broader program initiative launched at CEA/CESTA to introduce MDE to different domains such as high-performance computing [9,14] and graphical user interface for dataset edition [12].…”

Section: Introductionmentioning

confidence: 99%

Domain specific modeling for operations research simulation in a large industrial context

Lugato

Palyart

Engelvin

2012

Proceedings of the 2012 Workshop on Domain-Specific Modeling

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In order to conduct operations research studies on complex systems, CEA/CESTA 1 has been using and developing a new generation of simulator. The inherent complexity of such simulations ensues from the large spectrum of physical phenomena involved. As a consequence the description of a scenario and the analysis of parametric studies are timeconsuming tasks. In this paper, we illustrate how the use of modeling techniques can help users construct and interpret simulation scenarios, especially users who are not computer scientists. To that end, we present a domain-specific modeling language for operations research. Moreover its associated tool, which is deployed in a large industrial context, is introduced along with model examples.

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Improving Scalability and Maintenance of Software for High-Performance Scientific Computing by Combining MDE and Frameworks

Cited by 10 publications

References 11 publications

MDE in Practice for Computational Science

MDE in Practice for Computational Science

Using megamodeling to improve industrial adoption of complex MDE solutions

Domain specific modeling for operations research simulation in a large industrial context

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